Stefania Bracci

The paper identifies distinct computational constraints in lateral and ventral OTC for food representations, showing lateral regions prioritize action-related properties and ventral regions prioritize visual features.

The paper uses encoding models to reveal fine-grained feature selectivity in category-selective areas of the occipitotemporal cortex for bodies, hands, and tools.

The paper investigates action topography in visual cortex and DANNs, finding an action gradient in human brain regions that DANNs do not replicate.

This study investigates the human bias toward perceiving zoomorphic objects as animal-like and shows that this bias can be induced in deep neural networks with specific training.

This study records multi-unit spiking activity in human visual cortex to investigate body and body part representation, finding strong selectivity for bodies and generalization to non-photographic depictions.

The paper investigates the emergence of an animal appearance bias in human visual cortex using EEG, finding strong early neural responses to zoomorphic objects similar to animal pictures, supporting feedforward processing.

This paper compares the representational hierarchy of human and artificial visual systems, finding similarities in object-scene co-occurrence representations but differences in information processing strategies.

The paper investigates how hand-object orientation congruency affects neural activity during action planning using fMRI, finding increased premotor cortex activity for incongruent orientations.

This study compares how deep CNNs and human visual cortex represent object shape and category, finding that CNNs and the brain encode these features separately, with CNNs peaking in final layers and the brain in anterior ventral temporal cortex.

The paper shows that ventral visual cortex represents object appearance over animacy, unlike neural networks, which prioritize animacy in categorization.